An abundance of information is available on client-server networks, such as the Internet, Intranets, the World Wide Web (the “web”), other Wide and Local Area Networks (WANs and LANs), wireless networks, and combinations thereof, as examples, and the amount of information available on such client-server networks is continuously increasing. Further, users are increasingly gaining access to client-server networks, such as the web, and commonly look to such client-server networks (as opposed to or in addition to other sources of information) for desired information. For example, a relatively large segment of the human population has access to the Internet via personal computers (PCs), and Internet access is now possible with many mobile devices, such as personal digital assistants (PDAs), mobile telephones (e.g., cellular telephones), etc.
An increasingly popular type of technology for providing information to clients is known as “streaming media.” In general, streaming media presents data (e.g., typically audio and/or video) to a client in a streaming or continuous fashion. That is, with streaming media a client is not required to receive all of the information to be presented before the presentation begins. Rather, presentation of information in a streaming media file may begin before all of the file is received by the client, and as the received portion of the file is being presented, further portions of the file continue to be received by the client for later presentation. Thus, streaming media involves media (e.g., typically audio and/or video) that is transmitted from a server (e.g., a media server) to a client and begins playing on the client before fully downloaded.
Media servers are typically implemented for providing streaming media to clients. A “cluster” is often used to implement a media server. In general, a cluster is a group of nodes (e.g., servers and/or other resources) that appear to a user as a single system. For instance, a plurality of servers may be implemented as a cluster to form a single media server for serving streaming media files to requesting clients. While a plurality of different servers are used for servicing the clients' requests, to each client the cluster appears to be a single media server (i.e., it appears to the clients that they are accessing a single media server). Such cluster computing may be implemented to provide high availability (e.g., through redundancy provided by the plurality of nodes), parallel processing, and/or load balancing. Various load balancing strategies may be used for a cluster, including as examples a round-robin strategy or a “locality-aware” strategy, e.g., Locality-Aware Request Distribution (“LARD”) strategy.
Various streaming media files may be provided concurrently by a media server to various different clients. That is, a plurality of clients may concurrently access streaming media files from the media server. Of course, limits exist as to how many concurrent streams a media server can support for a given client population. That is, limits exist as to the capacity of a media server, even a clustered media server, for supporting a given “workload” (i.e., a number of concurrent client accesses of streaming media from the media server). Streaming media service providers have traditionally had difficulty in evaluating whether a given media server configuration (e.g., a server implementation having a certain size of memory, certain disk configuration, certain number of nodes in a cluster, etc.) provides sufficient capacity for supporting the service providers' workload as desired. Thus, streaming media service providers have traditionally had difficulty in evaluating different media server configurations for capacity planning to, for example, determine the most cost-effective configuration that is capable of supporting the service providers' media service workload.